5 Reasons why your important data assets shouldn't live in Excel.

A recent article in ArsTechnica revealed that even in the high-tech, data-driven world of F1, Excel was the go-to platform for managing massive inventories. If you think that your organisation is also overly dependent on spreadsheets, you're not alone. Many organisations have turned spreadsheets into databases for mission-critical data, but just because everyone's doing it doesn't mean it's a good idea.

In this post, we look at 5 reasons why your important data shouldn't live in Excel and offer a few suggestions on how to approach data asset management more sustainably.

1. Single source of truth:

We've all experienced not knowing which version of a file is the most up-to-date or accidentally using or sharing an old version of something. Excel's ability to copy, duplicate, and rename files makes it a poor option for maintaining a system of record or a single version of the truth. When you combine Excel spreadsheets with multiple users, you quickly lose trust in the integrity of the data.

2. Scalability

Did you know that Excel maxes out at 1,048,576 rows? Whilst this sounds like a lot, we all know what it's like when your computer crashes trying to open a particularly large spreadsheet. It's just not made for handling large datasets. If you see the spinning wheel of death when you open a spreadsheet, it could be time for a more robust solution, not a faster computer.

3. Stability

Spreadsheets are susceptible to corruption. Excel files can become corrupted for various reasons related to file size, macros and malware. While version control and backups can help, corruption jeopardises the availability of your data and, therefore, poses a risk to the decisions that it enables.

4. Integration

The value of datasets increases when they are combined with other datasets for new use cases or to create new data products. Spreadsheets aren't a good tool if you're looking to run analytics on multiple data sources, as they keep your data siloed and make it harder to maximise its value.

5. Data validation

We've all seen spreadsheets with three different types of date formats in use and felt the pain of trying to get answers from a spreadsheet full of blanks. Although Excel has some data validation tools, they need to be more extensive to ensure the validity of important data.

Despite these issues, even some of the most data-driven teams are guilty of using Excel for storing their mission-critical data. However, doing so puts the condition of your data at risk, eroding trust and potential value. Poor-quality data is also costly, according to Gartner research, the average financial impact of poor data quality on organisations is?$9.7 million annually.

To avoid these pitfalls, whether you're a business leader or a data leader, you should be considering the following:

1. What are my most important data assets for achieving my organisation's goals?
2. What condition do they need to be in for us to be successful?
3. Is the way these assets are being managed placing their condition at risk?

Anmut helps you identify and focus on the most important data assets that drive value for your organisation and put the right data asset management capabilities in place to ensure they stay fit for purpose and performance.

Find out more about data condition and why it matters here.